Increased Water Storage in the Qaidam Basin, the North Tibet Plateau from GRACE Gravity Data

published_or_final_versio

More severe hydrological drought events emerge at different warming levels over the Wudinghe watershed in northern China

Assessment of changes in hydrological droughts at specific warming levels is important for an adaptive water resources management with consideration of the 2015 Paris Agreement. However, most studies focused on the response of drought frequency to the warming and neglected other drought characteristics, including severity. By using a semiarid watershed in northern China (i.e., Wudinghe) as an example, here we show less frequent but more severe hydrological drought events emerge at 1.5, 2 and 3&thinsp;∘C warming levels. We used meteorological forcings from eight Coupled Model Intercomparison Project Phase 5 climate models under four representative concentration pathways, to drive a newly developed land surface hydrological model to simulate streamflow, and analyzed historical and future hydrological drought characteristics based on the standardized streamflow index. The Wudinghe watershed will reach the 1.5, 2 and 3&thinsp;∘C warming levels around 2015–2034, 2032–2051 and 2060–2079, with an increase in precipitation of 8&thinsp;%, 9&thinsp;% and 18&thinsp;% and runoff of 27&thinsp;%, 19&thinsp;% and 44&thinsp;%, and a drop in hydrological drought frequency of 11&thinsp;%, 26&thinsp;% and 23&thinsp;% as compared to the baseline period (1986–2005). However, the drought severity will rise dramatically by 184&thinsp;%, 116&thinsp;% and 184&thinsp;%, which is mainly caused by the increased variability in precipitation and evapotranspiration. The climate models and the land surface hydrological model contribute to more than 80&thinsp;% of total uncertainties in the future projection of precipitation and hydrological droughts. This study suggests that different aspects of hydrological droughts should be carefully investigated when assessing the impact of 1.5, 2 and 3&thinsp;∘C global warming.</p

Group Sparse Recovery via the ℓ0(ℓ2) Penalty: Theory and Algorithm

In this work we propose and analyze a novel approach for recovering group sparse signals, which arise naturally in a number of practical applications. It is based on regularized least squares with an ℓ0(ℓ2) penalty. One distinct feature of the new approach is that it has the built-in decorrelation mechanism within each group, and thus can handle the challenging strong inner-group correlation. We provide a complete analysis of the regularized model, e.g., the existence of global minimizers, invariance property, support recovery, and characterization and properties of block coordinatewise minimizers. Further, the regularized functional can be minimized efficiently and accurately by a primal dual active set algorithm with provable global convergence. In particular, at each iteration, it involves solving least squares problems on the active set only, and merits fast local convergence, which makes the method extremely efficient for recovering group sparse signals. Extensive numerical experiments are presented to illustrate salient features of the model and the efficiency and accuracy of the algorithm. A comparative experimental study indicates that it is competitive with existing approaches

Approximate perturbed direct homotopy reduction method: infinite series reductions to two perturbed mKdV equations

An approximate perturbed direct homotopy reduction method is proposed and applied to two perturbed modified Korteweg-de Vries (mKdV) equations with fourth order dispersion and second order dissipation. The similarity reduction equations are derived to arbitrary orders. The method is valid not only for single soliton solution but also for the Painlev\'e II waves and periodic waves expressed by Jacobi elliptic functions for both fourth order dispersion and second order dissipation. The method is valid also for strong perturbations.Comment: 8 pages, 1 figur

Genome-wide profiling of uncapped mRNA

Gene transcripts are under extensive posttranscriptional regulation, including the regulation of their stability. A major route for mRNA degradation produces uncapped mRNAs, which can be generated by decapping enzymes, endonucleases, and small RNAs. Profiling uncapped mRNA molecules is important for the understanding of the transcriptome, whose composition is determined by a balance between mRNA synthesis and degradation. In this chapter, we describe a method to profile these uncapped mRNAs at the genome scale